Deep Learning: New Computational Modelling Techniques for Genomics

Overview

Journal Nat Rev Genet

Specialty Genetics

Date 2019 Apr 12

PMID 30971806

Citations 399

Authors

Gokcen Eraslan

Ziga Avsec

Julien Gagneur

Fabian J Theis

Affiliations

Soon will be listed here.

Abstract

As a data-driven science, genomics largely utilizes machine learning to capture dependencies in data and derive novel biological hypotheses. However, the ability to extract new insights from the exponentially increasing volume of genomics data requires more expressive machine learning models. By effectively leveraging large data sets, deep learning has transformed fields such as computer vision and natural language processing. Now, it is becoming the method of choice for many genomics modelling tasks, including predicting the impact of genetic variation on gene regulatory mechanisms such as DNA accessibility and splicing.

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